Engineering E. coli for large-scale production - Strategies considering ATP expenses and transcriptional responses

Metab Eng. 2016 Nov:38:73-85. doi: 10.1016/j.ymben.2016.06.008. Epub 2016 Jul 1.

Abstract

Microbial producers such as Escherichia coli are evolutionarily trained to adapt to changing substrate availabilities. Being exposed to large-scale production conditions, their complex, multilayered regulatory programs are frequently activated because they face changing substrate supply due to limited mixing. Here, we show that E. coli can adopt both short- and long-term strategies to withstand these stress conditions. Experiments in which glucose availability was changed over a short time scale were performed in a two-compartment bioreactor system. Quick metabolic responses were observed during the first 30s of glucose shortage, and after 70s, fundamental transcriptional programs were initiated. Since cells are fluctuating under simulated large-scale conditions, this scenario represents a continuous on/off switching of about 600 genes. Furthermore, the resulting ATP maintenance demands were increased by about 40-50%, allowing us to conclude that hyper-producing strains could become ATP-limited under large-scale production conditions. Based on the observed transcriptional patterns, we identified a number of candidate gene deletions that may reduce unwanted ATP losses. In summary, we present a theoretical framework that provides biological targets that could be used to engineer novel E. coli strains such that large-scale performance equals laboratory-scale expectations.

Keywords: ATP expense; Escherichia coli; Glucose limitation; Maintenance; Scale-up/scale-down; Transcriptional response.

MeSH terms

  • Adenosine Triphosphate / metabolism*
  • Batch Cell Culture Techniques / methods*
  • Biosynthetic Pathways / physiology
  • Computer Simulation
  • Escherichia coli / physiology*
  • Escherichia coli Proteins / metabolism
  • Glucose / metabolism*
  • Metabolic Engineering / methods*
  • Metabolic Flux Analysis / methods
  • Metabolic Networks and Pathways / physiology
  • Models, Biological*
  • Stress, Physiological / physiology
  • Transcription Factors / metabolism*

Substances

  • Escherichia coli Proteins
  • Transcription Factors
  • Adenosine Triphosphate
  • Glucose